In the diagnosis and treatment of certain human diseases by medical imaging, clinicians seek to make certain measurements and delineate the boundaries of certain structures (for example, cancer lesions, tumors, etc.) and normal organs in the body. The measurements are subject to the expert interpretation of a trained radiologist, but are suggested by patterns of contrast contained in planar medical images. Oncologists seek more quantitative measurements such as faster review times, better capturing of volumes, masses, etc. from the radiologists. Lesion delineation can be a source of uncertainly, since typically, the lesion delineation process involves an experienced physician, interpreting, and manually contouring computed tomography (CT) alone or combined with position emission tomography (PET) imaging, on a slice-by-slice basis. As a result, advanced quantitative metrics and automation are needed for the trained professionals reviewing the medical images. Current tools are too slow for the radiologists to provide these metrics for the oncologists on all patients.